Fu et al. [1]} recently proposed pan-cancer computational histopathology model for predicting mutations, tumor composition and prognosis. They classified the tissue origin across organ sites and provides highly accurate, spatially resolved tumor and normal distinction within a given slide. Afterwards, they used CNNs to extract histopathological patterns and accurately discriminates 28 cancer and 14 normal tissue types. Furthermore, they predicted whole genome duplications, focal amplifications and
deletions, as well as driver gene mutations. Experimental results demonstrate wide-spread correlations with gene expression indicative of immune infiltration and proliferation.
